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Real-time Twitter Data Analysis of Saudi Telecom Companies for Enhanced Customer Relationship Management


Shaheen Khatoon


Vol. 17  No. 2  pp. 141-147


In this research an automatic solution for helping telecommunication companies to gain better customer insight by utilizing real time Twitter data is proposed. To develop an enhanced Customer Relationship Management (CRM) in highly competitive market, it is very important for companies to understand how customers perceive and select specific services offer by them, compare to their competitors. While understanding the customer perception from conventional sources such as surveys, interviews and feedback is well studied and established, gaining insights from twitter is challenging due to several underlying issues in Twitter data, such as short message length, diverse colloquial linguistic patterns and representational richness. This study discusses the challenges of analyzing Twitter data and proposed a sentiment analysis approach to identify whether customers are enjoying with services or having bad experience. As a proof of concept, we present some preliminary results from telecommunication domain pertaining to three major Saudi companies, Mobily, Zain and Saudi Telecom Company (STC). To demonstrate the usefulness of work temporal and spatial changes towards sentiments of these companies are determined. This allow companies to monitor customer perception towards their own service and services provided by their competitors over time. Furthermore, by visualizing sentiment spatially in real-time, company can identify which region customer are having bad experience. This insight would allow companies to solve the problem in real-time fashion and provide better quality of service by redesigning product or service by considering the customer’s needs.


Sentiment analysis Twitter SentiWordNet Natural language processing CRM, Telecommunication